Automatic machine translation has been available for years thanks to services like Google Translate, but results have never been completely satisfying. Thanks to the recent progress made in deep learning, it is now possible to reach a more advanced level of machine translation based on AI.
AI models make translation very fluent. Even for advanced technical topics, it's hard to detect that translation was performed by a machine. Now that translation is more reliable than ever, it creates tons of new possibilities.
These last years, several advanced AI translation models were released, like NLLB 200 and M2M 100 by Meta, and Helsinki Opus MT by the University of Helsinki. On NLP Cloud you can use our translation API based on NLLB 200 to translate text in 200 languages.
Potential applications for automatic translation are countless, but let's show 2 examples.
This broadens their market reach, allowing them to cater to customers worldwide without the need for extensive multilingual customer support teams. It significantly enhances the shopping experience for non-English speakers and can dramatically increase a company’s international sales.
In the travel and hospitality industry, AI translation facilitates seamless communication between businesses and travelers from different linguistic backgrounds. This can range from translating hotel websites and booking platforms to providing real-time spoken language translation services for front desk staff or in tourist information centers.
AI-powered translation services in healthcare can translate patient records, informational brochures, and consent forms. They can also facilitate real-time communication between healthcare providers and patients who speak different languages.
In the educational sector, AI translation makes academic content and research accessible across linguistic boundaries. It enables the translation of textbooks, lectures, and research papers into multiple languages, facilitating global learning and collaboration.
NLP Cloud proposes a translation API based on AI that allows you to perform machine translation out of the box in 200 languages, based on Facebook's NLLB 200 3.3B. This model performs better than Meta's M2M100, and is on-par with Helsinki's Opus MT models. If you are not sure about the language of the input text you are trying to translate, you can let the model guess it for your.
For more details, see our documentation about translation here.
Here are the supported languages:
Testing deep learning translation locally is one thing, but using it reliably in production is another thing. With NLP Cloud you can just do both!